Academic journal article Informatica Economica

Smart Data Web Services

Academic journal article Informatica Economica

Smart Data Web Services

Article excerpt

In the new world where the Internet business resembles with a large and distributed sea of links, using Cloud architectural model, the web-service interoperability and SOA model one could deploy an arguably new class/generation of apps/services that could leverage the marriage of these originally distinct computing models to be real smart, as autonomous, dynamic and agile, but open to integrate and adapt.

Keywords: Web Services, Cloud Computing, SEO, SQL, XML

1 Introduction

The Web Service Technology seems to have passed the over-hype phase by trying to reach to the maturity level that will finally enable its mass adoption. The Cloud computing era could be the trigger factor to overspread the web services as the foundation or the platform of choice for the Internet applications or, at a larger scale, for the Internet business systems.

In this regard, we believe that in the context of the marriage with cloud computing paradigm, the web service architecture could achieve some special advantages in the following directions:

* data access openness and standardization;

* autonomy of underlying supporting infrastructure;

* dynamic search and discovery using the already widely spread searching technologies like SEO (as Search Engine Optimization).

In fact, we believe that a new web services generation could come (must come?) on the stage of the business applications and technologies, in order to leverage the true opportunity of Cloud architecture in the Internet-based business processes area. The Cloud services providers made some strides on storage and office-based applications, but for the actual business platforms and application services the big wave is yet to come over. In our opinion an enhanced support of business processes and business functions will have a major impact on the proliferation of the Cloud-based architectures. The current SaaS model (Software as a Service) that delivers business oriented applications has some serious limitations that slow down its adoption:

* preserving a quasi-monolithic approach regarding aggregation of the available business functions (integrated, but not enough modularized);

* deep dependency on the backend Cloud infrastructure (limited autonomy and agility);

* poor integration with other business oriented services, as they aren't built with large-scale inter-connectivity in mind, and preserving a quite inflexible layered architecture that is clearly delimited between the boundaries of a business system template (limited openness to interchange data protocols).

As we will argue in the followings, the "smartness" capacity of the new kind of web services will be sustained on a sum of characteristics coming from three service models (see Fig.1), characteristics as agility, openness, dynamic, autonomous.

These characteristics could leverage a higher architectural level consisting in smart data integration in the web context, meaning: no more proprietary drivers to access data sources, no more proprietary and private encrypted data formats, no more static referencing or integrating data sources (smart as dynamic discovery and reference of valuable data sources).

We think that the business oriented web services will have to deal with, among others, at least two fundamental challenges, as they are stated in the SOA blueprints:

* business processes control or orchestration; one potential initiative in this area could be a form of standardization of some kind of event-based web services (we intend to argue and develop such architecture in a future paper);

* data query, data interchange and data management; the current paper will try to argue and outline a possible feasible architecture.

Concerning the special kind of data centric web services, we think that they have some characteristics that could make them even better suited with/into cloud based architectures, because:

* they are structured (borrowing some features from databases interoperability with traditional data oriented software components of the business systems) thus assuming:

* structured (or, at least, semi-structured) data definitions (metadata);

* structured and declarative data requests;

* they are data intensive:

* taking into account the large data amount to interchange;

* taking into account the data integration issues (the need for interchangeable data format);

* taking into account the large data amount for storage;

* taking into account the data processing computing capabilities (such as OLAP or Data Mining);

* they could be integrated into larger/ aggregate/composed/derived structural architectures, thus implying:

* data consolidation of heterogeneous data systems (integrated OLTP systems);

* data aggregation for analytical processing specific to decision-making business processes (such as OLAP-based systems). …

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